Improved security, it has been argued, consists in getting more dots and in the joining them up in a timely manner. In this paper we argue that such an approach rapidly leads to computationally intractable intelligence tasks and does not actually deliver what is needed. We take timely pattern processing to be the main intelligence task—computationally speaking, an even more daunting prospect. After discussing the nature of the problem in the light of Ashby’s Law of Requisite Variety, we introduce the concept of Global Neighborhood Watch as a socially distributed pattern processing strategy. We show how the application of filters that privilege certain contexts, vantage points, and time frames, in conjunction with a distributed intelligence process drawing on modern “citizen” technologies can rapidly home in on relevant security threats. We illustrate the process by means of an imaginary case and discuss the policy implications that it raises. A conclusion follows.